Indonesia#

The first application of FEO Global is the development of an openly available electricity systems model for Indonesia. This model is used to explore transition pathways to a net-zero electricity system. As with all energy system models, the inputs include a range of datasets and assumptions (e.g. technology cost projections, discount rates). All of these inputs are described here in order to allow for the model to be reviewed, re-run, and re-purposed.

Model scope#

The model aims to represent the electricity system of Indonesia as accurately as possible, subject to constraints on data and computation time. The main aspects that improve the accuracy of the model’s representation of Indonesia’s electricity system are its spatial and temporal resolution.

Spatial resolution#

The model represents all 34 provinces of Indonesia across 7 regions - shown in the table and map below - as individual nodes.

Provinces of Indonesia#

Region

Province

Province (English)

Model code

Jawa

Banten

Banten

IDNBT

Jawa

Jakarta Raya

Jakarta

IDNJK

Jawa

Jawa Barat

West Java

IDNJB

Jawa

Jawa Tengah

Central Java

IDNJT

Jawa

Jawa Timur

East Indonesia

IDNJI

Jawa

Yogyakarta

Yogyakarta

IDNYO

Kalimantan

Kalimantan Barat

West Kalimantan

IDNKB

Kalimantan

Kalimantan Selatan

South Kalimantan

IDNKS

Kalimantan

Kalimantan Tengah

Central Kalimantan

IDNKT

Kalimantan

Kalimantan Timur

East Kalimantan

IDNKI

Kalimantan

Kalimantan Utara

North Kalimantan

IDNKU

Maluku

Maluku

Maluku

IDNMA

Maluku

Maluku Utara

North Maluku

IDNMU

Nusa Tenggara

Bali

Bali

IDNBA

Nusa Tenggara

Nusa Tenggara Barat

West Nusa Tenggara

IDNNB

Nusa Tenggara

Nusa Tenggara Timur

East Nusa Tenggara

IDNNT

Papua

Papua

Papua

IDNPA

Papua

Papua Barat

West Papua

IDNPB

Sulawesi

Gorontalo

Gorontalo

IDNGO

Sulawesi

Sulawesi Selatan

South Sulawesi

IDNSN

Sulawesi

Sulawesi Tengah

Central Sulawesi

IDNST

Sulawesi

Sulawesi Tenggara

Southeast Sulawesi

IDNSG

Sulawesi

Sulawesi Utara

North Sulawesi

IDNSA

Sulawesi

Sulawesi Barat

West Sulawesi

IDNSR

Sumatera

Aceh

Aceh

IDNAC

Sumatera

Bengkulu

Bengkulu

IDNBE

Sumatera

Jambi

Jambi

IDNJA

Sumatera

Kepulauan Bangka Belitung

Bangka-Belitung

IDNBB

Sumatera

Kepulauan Riau

Riau Islands

IDNKR

Sumatera

Lampung

Lampung

IDNLA

Sumatera

Riau

Riau

IDNRI

Sumatera

Sumatera Barat

West Sumatra

IDNSB

Sumatera

Sumatera Selatan

South Sumatra

IDNSS

Sumatera

Sumatera Utara

North Sumatra

IDNSU

_images/Indonesia_provinces_english.png

Temporal resolution#

Each year is divided into 6 ‘Seasons’ [S1-S6]:

Teporal resolution - Seasons#

Season

Months

S1

Jan, Feb

S2

Mar, Apr

S3

May, Jun

S4

Jul, Aug

S5

Sep, Oct

S6

Nov, Dec

Each ‘Season’ is further divided into 12 ‘Daily Time Brackets’:

Temporal resolution - daily time brackets#

Daily time bracket

Hours of the day

D1

0, 1

D2

2, 3

D3

4, 5

D4

6, 7

D5

8, 9

D6

10, 11

D7

12, 13

D8

14, 15

D9

16, 17

D10

18, 19

D11

20, 21

D12

22, 23

Together, there are 72 representative ‘timeslices’ in the model. The temporal resolution is the same for the entire model period.

Model horizon#

Base year - 2021

End year - 2050

Key assumptions#

Discount rates#

The model includes two types of discount rates (DR): ‘social’ and ‘financial’. The social DR is applied across the entire model and represents the relative weighting of present and future costs and benefits. A low social DR weights the present and the future more similarly than a high DR. The financial DR is technology-specific and represents the weighted average cost of capital (WACC) for a given technology (e.g. power plant). The model assumes a value of 10% for both the social and financial discount rates. The latter is based on the IEA Cost of Capital Observatory

Reserve Margin#

The Reserve margin decreases from the current level of 60% to 35% by 2030.

Data#

Technology costs#

Battery costs from NREL All other costs from OSeMOSYS Global and PLEXOS World.

Technology cost projections (Capital)#

Technology

Unit

2021

2030

2040

2050

BAT

USD2020/kWh

330

198

173

149

BIO

USD2020/kW

2038

2038

2013

2013

CCG

USD2020/kW

790

790

790

790

COA

USD2020/kW

1442

1442

1442

1442

COG

USD2020/kW

1030

1030

1030

1030

CSP

USD2020/kW

3088

3088

2675

2675

GEO

USD2020/kW

2625

2625

2513

2513

HYD

USD2020/kW

2088

2088

2113

2113

OCG

USD2020/kW

425

425

425

425

OIL

USD2020/kW

1240

1240

1240

1240

OTH

USD2020/kW

1240

1240

1240

1240

PET

USD2020/kW

1240

1240

1240

1240

SPV

USD2020/kW

723

723

615

615

URN

USD2020/kW

3263

3263

3200

3200

WAS

USD2020/kW

6663

6663

6550

6550

WAV

USD2020/kW

4475

4475

3350

3350

WOF

USD2020/kW

2355

2355

1968

1968

WON

USD2020/kW

1513

1513

1475

1475

Renewable Energy Profiles#

Hourly renewable energy profiles for wind (onshore and offshore) and solar PV in each province were obtained from renewables.ninja. Data for 2020 was used.

Renewable Energy Potentials#

Data on renewable energy potentials by province was obtained from multiple sources:

Renewable energy potential#

Potential (GW) by province

Solar photovoltaic

Wind - Onshore

Hydropower

Biomass

Geothermal

Banten

175.94

1.21

4.67

0.93

1.31

Jakarta Raya

11.60

0.02

0.09

0.02

0.03

Jawa Barat

11.97

0.00

0.11

0.34

0.64

Jawa Tengah

55.70

0.00

0.85

0.35

0.03

Jawa Timur

11.97

0.01

1.01

0.02

0.04

Yogyakarta

5.98

0.00

0.00

0.01

0.00

Kalimantan Barat

249.47

0.00

0.65

2.06

1.05

Kalimantan Selatan

40.91

0.42

1.45

0.36

6.63

Kalimantan Tengah

54.23

0.19

1.27

0.11

1.83

Kalimantan Timur

66.69

0.21

1.31

0.16

1.16

Kalimantan Utara

983.49

0.00

6.54

3.00

0.05

Maluku

193.80

0.09

0.93

0.87

0.00

Maluku Utara

586.46

0.00

2.49

3.77

0.00

Bali

1100.71

0.00

6.63

2.40

0.00

Nusa Tenggara Barat

135.59

0.00

5.01

0.55

0.00

Nusa Tenggara Timur

209.08

0.00

0.00

0.23

0.03

Papua

20.49

0.00

0.00

0.66

0.00

Papua Barat

64.98

0.00

0.47

1.65

2.86

Gorontalo

196.59

4.86

0.55

0.06

0.23

Sulawesi Selatan

81.05

0.00

0.18

0.01

0.23

Sulawesi Tengah

40.58

0.03

0.03

0.07

0.14

Sulawesi Tenggara

312.49

5.94

0.24

0.14

1.04

Sulawesi Utara

571.50

0.16

19.98

0.36

0.03

Sulawesi Barat

149.57

0.00

2.42

0.15

0.03

Aceh

261.47

0.00

0.14

4.67

0.03

Bengkulu

86.06

6.53

2.65

0.11

0.32

Jambi

156.68

0.00

4.55

0.06

0.37

Kepulauan Bangka Belitung

195.25

0.00

1.10

0.06

0.30

Kepulauan Riau

14.04

0.00

0.00

0.00

0.87

Lampung

72.76

0.00

2.87

1.00

1.62

Riau

389.52

0.00

0.97

5.00

1.91

Sumatera Barat

213.06

0.04

4.98

1.43

3.63

Sumatera Selatan

7.35

0.00

0.06

0.01

0.01

Sumatera Utara

22.27

0.00

0.89

0.11

0.00

Electricity demand projections#

Electricity demands for all 34 provinces, current and projected, are inputs to the model. Electricity demand by province for 2021 is obtained from the RUPTL 2021-2030. The methodology used to project these demands between 2021-2050 is detailed here and summarised below.

Electricity demand projections (GWh)#

Province

Model code

2021

2025

2030

2040

2050

Banten

IDNBT

23831

27125

31314

41882

56285

Jawa Barat

IDNJB

53318

55595

58492

65137

72835

Jawa Timur

IDNJI

39457

41847

44887

51966

60358

Jakarta Raya

IDNJK

32709

56416

86572

192336

449512

Jawa Tengah

IDNJT

26661

26954

27327

28133

28964

Yogyakarta

IDNYO

3108

8022

14272

38962

110752

Kalimantan Barat

IDNKB

2913

4156

5900

9907

17475

Kalimantan Timur

IDNKI

4049

5840

8350

14305

26073

Kalimantan Selatan

IDNKS

3051

4413

6323

10866

19868

Kalimantan Tengah

IDNKT

1598

2254

3175

5220

8792

Kalimantan Utara

IDNKU

238

350

508

861

1485

Maluku

IDNMA

583

938

1300

2288

4145

Maluku Utara

IDNMU

637

1004

1380

2390

4263

Bali

IDNBA

4708

4896

5136

5716

6479

Nusa Tenggara Barat

IDNNB

2290

3623

4984

8592

15040

Nusa Tenggara Timur

IDNNT

1160

1843

2541

4451

8131

Papua

IDNPA

1238

1960

2699

4687

8373

Papua Barat

IDNPB

583

932

1288

2312

4460

Gorontalo

IDNGO

639

793

1025

1704

2857

Sulawesi Utara

IDNSA

1940

2446

3206

5454

9344

Sulawesi Tenggara

IDNSG

6598

8285

10822

18315

31268

Sulawesi Selatan

IDNSN

1354

1679

2168

3612

6117

Sulawesi Tengah

IDNST

1150

1430

1851

3264

6415

Aceh

IDNAC

3074

4284

5676

9738

16847

Kepulauan Bangka Belitung

IDNBB

1369

1877

2460

4179

7246

Bengkulu

IDNBE

1059

1474

1952

3371

5959

Jambi

IDNJA

2112

2952

3919

6744

11700

Kepulauan Riau

IDNKR

3479

4934

6608

13141

27719

Lampung

IDNLA

5177

7215

9559

16361

28107

Riau

IDNRI

6108

8130

10454

17263

29251

Sumatera Barat

IDNSB

3646

5145

6868

11909

20720

Sumatera Selatan

IDNSS

5594

7879

10507

18177

31532

Sumatera Utara

IDNSU

11748

16509

21983

38639

70244

Sulawesi Barat

IDNSR

439

547

709

1181

1973

Fuel Prices#

Fuel price projections#

Fuel

Unit

2020

2030

2040

2050

Coal

USD2020/mt

60.8

194.24

194.24

194.24

Natural gas

USD2020/mmbtu

3.2

23.86

23.86

23.86

Oil

USD2020/bbl

42.3

76.94

76.94

76.94

Scenarios#

The model was used to explore three scenarios: Current Policies [CP], Least-cost [LC], and Net-Zero [NZ]. The scenarios represent alternate pathways for the expansion of Indonesia’s electricity system. Each scenario consists of a set of assumptions and constraints, as detailed below:

Current policies (TBC)#

This scenario includes all implemented policies related to the expansion of Indonesia’s electricity system as well as committed power plants.

Least-cost#

This represents an ‘unconstrained’ development of the electricity system. It does not include any emission or renewable energy targets. Planned powerplants are provided as ‘options’ to invest in but are not forced into the model.

Net-zero#

This scenario includes an explicit target of reaching net-zero emissions by 2050, with peak emissions in 2040.

Results#

Capacity expansion#

BAU

Net-zero

Annual electricity generation mix#

BAU

Net-zero

Hourly electricity generation mix#

BAU

Net-zero

Planned improvements#

  • Plant-specific efficiencies

  • Hydropower capacity factor by plant / node

  • Technology-specific discount rates

  • Multiple weather years

  • Province-specific demand profiles

Model code, data, and workflow#

The entire workflow of FEO Global is available on GitHub under an open license (AGPL v3.0) at transition-zero/feo-esmod-osemosys. In addition, it uses only publicly available data and an open source solver (CBC).

References#